How Healthy Is Your Data?

This year, Esri’s free data health checks will be offered for water and wastewater, as well as land records, at the ArcGIS for You island. Industry experts will run an analysis on your data in a file or personal geodatabase and provide a report of any error findings. You can sign-up by emailing datareviewer@esri.com.

At the 2011 Esri UC, the GIS team from the City of Woodland—a 55,000-population town in California—took advantage of Esri’s free data health checks for water and wastewater.

“That short session really opened our eyes to the state of our data,” said Daniel Hewitt, the city’s GIS specialist. “We were not anywhere near where we thought we should be and wanted to fix that.”

Originally, most of the city’s GIS infrastructure data was ported over from CAD by a third-party contractor into a generic data model. The transition created issues mainly in regards to topology, attribute population, and schema structure. For the last three years, the GIS team has been focused on customizing the schema fields and populating attribute values from historical hard-copy drawings.

Meanwhile the city identified the need for field crew members to update attribute values in the production database while in the field. Field crew members are also required to submit spatial changes to the GIS staff for processing through a redlining process. The GIS team wanted to define and standardize a systematic QA/QC process to validate data imported from CAD as well as to efficiently process change requests from the field.

During the data health check, a water utilities expert from Esri used the ArcGIS Data Reviewer extension to configure business rules specific to the city’s needs. The city decided to purchase ArcGIS Data Reviewer.

Errors are detected where valve diameters do not match the connecting mains.

Now, the City of Woodland uses ArcGIS Data Reviewer to find and fix any errors in feature classes that need more attention. The technology upgrade has made a significant impact in the water infrastructure features as well as other base map layers such as the city’s parcel feature class. The city is now in the process of building a master QA/QC plan centered on integrating Data Reviewer into their SDE geodatabase.

In addition to monetary savings, implementing ArcGIS Data Reviewer has resulted in better data quality and confidence that the data has been fully reviewed. Feature classes that were once thought to be in good shape need to be edited to be up to par. Since most of the issues are related to attribution, the city has identified the need to invest significant amount of time in finding and fixing issues that the GIS team believes can be overcome with the help of ArcGIS Data Reviewer.

As part of a co-op agreement, the city is required to share parcel information with the county. The time it takes for the county office to find and fix any QA/QC errors within the parcel data is charged to the city. With ArcGIS Data Reviewer, the GIS team is confident the data has been validated according to the county’s needs. Therefore the city avoids additional charges—another significant achievement.

“We can now perform consistent QA/QC tasks and keep our data in top shape after we have done the initial time investment,” Hewitt said.